Large skull defects arise frequently following trauma, cancer, stroke, and birth defect reconstructive surgery. Intra-operative repair is time-consuming and often results in sub-optimal cosmesis and insufficient protection from trauma and infection. Recently, CT data has been used to three- dimensionally (3D) render full-size, anatomically-accurate, models of patient skulls for pre-surgical use in manual implant design and production. We propose an improved, cost-effective, and automated process for rapid manufacture of neurocranial implants. We wish to determine the most important elements necessary for real-time skull implant design and manufacture. We hypothesize: (1) that mechanical imaging frames can verify scanner 3D CT accuracy and lack of patient motion, thereby facilitating automated skull identification, (2) that automatic delineation of a skull defect margin can determine implant fit, and (3) that a left-right mirrored or average skull image can effectively determine the implant's surface shape. To address these hypotheses we propose to test the reliability and accuracy of automated and manual implant production methods. We expect that custom implants could outperform off-the-shelf and intra-operative solutions by reducing initial cost, operating room time, and improving overall post-surgical outcome. PROPOSED COMMERCIAL APPLICATIONS: The immediate commercial application is the production of an implant to custom-fill any shape of large skull deficit. CT scan data can be readily obtained from standard imaging devices and computer equipment available at most hospitals. After centrally processing the data and confirmation of the preliminary design by the treating physician, a sterile prosthetic implant can be delivered by overnight mail.